Here’s the difference between Starburst and Databricks. The comparison is based on pricing, deployment, business model, and other important factors.
Starburst queries data across any database, making it instantly actionable for data-driven organizations. With Starburst, teams can lower the total cost of their infrastructure and analytics investments, prevent vendor lock-in, and use the existing tools that work for their business. Trusted by companies like Comcast, FINRA, and Condé Nast, Starburst helps companies make better decisions faster on all data.
Databricks provides a data lakehouse that unifies your data warehousing and AI use cases on a single platform. With Databricks, you can implement a common approach to data governance across all data types and assets, and execute all of your workloads across data engineering, data warehousing, data streaming, data science, and machine learning on a single copy of the data. Built on open source and open standards, with hundreds of active partnerships, Databricks easily integrates with your modern data stack. Additionally, Databricks uses an open standards approach to data sharing to eliminate ecosystem restrictions. Finally, Databricks provides a consistent data platform across clouds to reduce the friction of multicloud environments. Today, Databricks has over 7000 customers, including Amgen, Walmart, Disney, HSBC, Shell, Grab, and Instacart.
|Categories||Data Lakes, Data Mesh||Data Warehouses, Data Lakes|
|Stage||Mid Stage||Late Stage|
|Target Segment||Enterprise, Mid size||Enterprise, Mid size|
|Pricing||Contact Sales||Freemium, Contact Sales|
|Location||US||San Francisco, US|
|Companies using it|